Fighter pilots call it the “sound of freedom” — the loud, thundering growl of a jet engine as a plane accelerates. To the pilots, that sound is an affirmation that their planes will have plenty of power to outmaneuver any enemy. To most average folks, however, that sound is sheer noise, loud and painful. To the men and women on the deck of an aircraft carrier, in particular, it can even be a health hazard, leading to permanent hearing loss.
Enter Stanford professor Sanjiva Lele, who holds a joint appointment in the departments of Aeronautics and Astronautics, and Mechanical Engineering. Lele is one of the world’s foremost experts on the mechanics of engine noise. He has produced some of the most sophisticated computer models in use today to predict when loud noises will occur during flight and help designers reduce noise while improving engine thrust and efficiency. His field has come to be known as “aeroacoustics.”
Computer simulations in aerodynamics first came into vogue in the 1970s and they changed the industry. But the related field of aeroacoustics has only relatively recently ascended to prominence, thanks in part to Lele and others who are mastering the mathematical complexities of the vibrations in air caused by turbulence. “We’ve unraveled the puzzle of how sound leaks out from high-speed jets,” Lele says.
The U.S. Navy spends great sums each year treating those with hearing loss and is acutely interested in reducing the jet noise whenever possible. The Navy’s stated goal is a reduction of engine noise by 3 decibels in the near term. “That sounds like a modest number, but in fact represents a reduction in the apparent sound energy by almost half,” Lele adds.
Unlike commercial flights, which approach landing at relatively quiet speeds — almost at idle, Lele says — when a Navy jet approaches an aircraft carrier, it must maintain a relatively high engine speed in case it must abort and zoom back into the sky to save a $60 million aircraft and its pilot.
“Consequently, the deck of an aircraft carrier is a terrible sound environment for those sailors,” says Lele, who came to Stanford in 1990 after a postdoctoral stint at NASA. “We solved the mystery of one of the more challenging acoustic phenomena of jet noise known as crackle.”
Crackle is produced by sharp, shock-like compression in the air. Sudden like sonic boom, crackle is “particularly irritating” to listeners, Lele says. What’s more, crackle accounts for up to 30 percent of the overall sound of a jet engine in its peak direction. Eliminating crackle alone could reduce peak jet noise by anywhere from 3 to 4 decibels.
Crackle had been the object of some debate in the engineering community. It was unclear whether the sound came from within the supersonic jet itself, or whether it was an acoustic phenomenon in which the sound waves compound upon themselves outside the engine to produce the spikes in sound.
In simple terms, jet noise is caused by the mixing of hot, fast-moving exhaust as it exits the engine and the colder, slow-moving air outside. The mixing happens in swirling eddy patterns — otherwise known as turbulence — producing vibrations and sound. These eddies start out small, but grow larger and more complex as they move away from the jet nozzle over time.
The challenge from a computational standpoint, Lele says, is accurately capturing these patterns in three dimensions. In this respect, Lele and his cohort in the field have come to understand both the physics of turbulence and the mathematics necessary to describe these phenomena at precisely a point in time when the computational power of computers is such that highly accurate computational simulations are possible.
Lele’s simulations with postdoctoral scholar Joseph Nichols showed conclusively that the sound of crackle emanates very close to the jet, directly from the jet turbulence itself, where cool air rejoins the hot jet flow. For this and other groundbreaking contributions to the field, Lele received the prestigious Aeroacoustics Award for 2016 from the American Institute of Aeronautics and Astronautics. “We aren’t designing new engines or new aircraft, but our work removes some of the mystery from the subject,” Lele says.
Using Lele’s models, designers can run simulations on specific designs to better explore which are more likely to reduce noise in the real world. Such simulations can greatly reduce the testing necessary once a new design is produced or an existing design is modified, and therefore can have a great impact on research and development costs. “The trick,” Lele says, “is not just to know when a particular sound will occur, but to explain why it occurs. Often, that’s the difficult part.”
Noise is a major annoyance in aviation specially if you want to go fast, but industry has to meet stringent regulations concerning permissible sound levels. Can designers continue to create larger, faster aircraft that nonetheless meet or exceed civilian noise thresholds? “That’s a big challenge,” Lele said. “Simulations can help turn that vision into a reality.”
Lele is now adapting his knowledge of fluid dynamics and air flows as they relate to jet noise to a new and down to earth challenge — optimizing the power output from wind farms. “Both problems involve questions of turbulent flows, from small scales that are very irregular to large scales that are more orderly. What matters is not how a single turbine will perform, but how a system — a farm — of hundreds or maybe thousands of turbines will perform over time,” Lele says.
He has been collaborating with Stanford Engineering faculty member John Dabiri who is working on optimal turbine design and placement – inspired by the fluid mechanics of animals like fish and birds moving as a group in unison.
Modeling a wind farm is considerably more complex than modeling a single turbine and multiplying it by the number of turbines in the field. Lele explains that turbines on the leading edge of the farm might perform as expected, but those to lee – downwind – will not because the upwind turbines have sapped energy and created wakes. These effects reduce efficiency in subsequent turbines. They also exert structural stresses that can lead to mechanical breakdown much sooner than expected. Both consequences harm the economic efficiency of the farms.
These flows are very complex, even more so than those from a jet engine. After all, the wind condition at a wind farm site is only one element of the local weather. Still, the models must accurately predict the outcomes, often over a period of years or even decades.
“The power output changes with wind strength and direction. The landscape changes the wind. Nighttime is different from the day. Sometimes the sun is shining, sometimes not. There are different atmospheric conditions and all of this has to be modeled,” Lele says.
Existing tools are not very reflective of what actually happens in nature. When several large European wind farms were built 15 to 20 years ago, actual power output was 40 to 60 percent short of estimates predicted by the best models in use at the time — a significant shortfall that impacted the long-term economics of those farms.
Recently models based on larger-scale weather prediction coupled to local simulations of the atmosphere have been proposed. They should have improved accuracy, but they are computationally intensive — that is, they would take a lot of processor power and are, therefore, very expensive. Lele, with his PhD student Aditya Ghate, has been developing new types of models to achieve acceptable accuracy while reducing the computational cost, by combining what he knows from aeroacoustics and what we know about boundary layer turbulence in the atmosphere.
“So far, we’ve been able to achieve about a thousand-fold reduction in the cost while retaining a good accuracy overall,” Lele says.
Asked to explain why he made the leap from jet noise to wind farms, Lele says: “It’s fun, to apply knowledge from one field to something new that you’ve never tried before to make a difference in the world. That is engineering.”